Primary exercises
- In the survey dataset add a new column
feet with heights reported in feet unit (1 foot = 30.48 cm).
mutate(survey, feet=height/30.48)
# A tibble: 233 × 14
name gender span1 span2 hand fold pulse clap exerc…¹ smokes height m.i age
<chr> <chr> <dbl> <dbl> <chr> <chr> <dbl> <chr> <chr> <chr> <dbl> <chr> <dbl>
1 Alys… female 18.5 18 right right 92 left some never 173 metr… 18.2
2 Todd male 19.5 20.5 left right 104 left none regul 178. impe… 17.6
3 Gera… male 18 13.3 right left 87 neit… none occas NA <NA> 16.9
4 Robe… male 18.8 18.9 right right NA neit… none never 160 metr… 20.3
5 Dust… male 20 20 right neit… 35 right some never 165 metr… 23.7
6 Abby female 18 17.7 right left 64 right some never 173. impe… 21
7 Andre male 17.7 17.7 right left 83 right freq never 183. impe… 18.8
8 Mich… female 17 17.3 right right 74 right freq never 157 metr… 35.8
9 Edwa… male 20 19.5 right right 72 right some never 175 metr… 19
10 Carl male 18.5 18.5 right right 90 right some never 167 metr… 22.3
# … with 223 more rows, 1 more variable: feet <dbl>, and abbreviated variable name
# ¹exercise
- In the survey dataset add a new column
diffWritingHandSpan : the difference of span1 (writing hand) and span2 (non-writing hand).
mutate(survey, diffWritingHandSpan=span1-span2)
# A tibble: 233 × 14
name gender span1 span2 hand fold pulse clap exerc…¹ smokes height m.i age
<chr> <chr> <dbl> <dbl> <chr> <chr> <dbl> <chr> <chr> <chr> <dbl> <chr> <dbl>
1 Alys… female 18.5 18 right right 92 left some never 173 metr… 18.2
2 Todd male 19.5 20.5 left right 104 left none regul 178. impe… 17.6
3 Gera… male 18 13.3 right left 87 neit… none occas NA <NA> 16.9
4 Robe… male 18.8 18.9 right right NA neit… none never 160 metr… 20.3
5 Dust… male 20 20 right neit… 35 right some never 165 metr… 23.7
6 Abby female 18 17.7 right left 64 right some never 173. impe… 21
7 Andre male 17.7 17.7 right left 83 right freq never 183. impe… 18.8
8 Mich… female 17 17.3 right right 74 right freq never 157 metr… 35.8
9 Edwa… male 20 19.5 right right 72 right some never 175 metr… 19
10 Carl male 18.5 18.5 right right 90 right some never 167 metr… 22.3
# … with 223 more rows, 1 more variable: diffWritingHandSpan <dbl>, and abbreviated
# variable name ¹exercise
- In the pulse dataset add new weight variables
pound and stone (1 kg = 2.20462 pound = 0.157473 stone).
mutate(pulse, pound = weight * 2.20462, stone = weight * 0.157473 )
# A tibble: 110 × 15
id name height weight age gender smokes alcohol exerc…¹ ran pulse1 pulse2
<chr> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
1 1993_A Bonn… 173 57 18 female no yes modera… sat 86 88
2 1993_B Mela… 179 58 19 female no yes modera… ran 82 150
3 1993_C Cons… 167 62 18 female no yes high ran 96 176
4 1993_D Trav… 195 84 18 male no yes high sat 71 73
5 1993_E Lauri 173 64 18 female no yes low sat 90 88
6 1993_F Geor… 184 74 22 male no yes low ran 78 141
7 1993_G Cher… 162 57 20 female no yes modera… sat 68 72
8 1993_H Fran… 169 55 18 female no yes modera… sat 71 77
9 1993_I Sonja 164 56 19 female no yes high sat 68 68
10 1993_J Troy 168 60 23 male no yes modera… ran 88 150
# … with 100 more rows, 3 more variables: year <dbl>, pound <dbl>, stone <dbl>, and
# abbreviated variable name ¹exercise
- In the survey dataset convert the variables
smokes from character to factor with levels {“never”,“occas”,“regul”, “heavy”}, in that order.
mutate(survey, smokes = fct_relevel(factor(smokes), "never","occas","regul", "heavy"))
# A tibble: 233 × 13
name gender span1 span2 hand fold pulse clap exerc…¹ smokes height m.i age
<chr> <chr> <dbl> <dbl> <chr> <chr> <dbl> <chr> <chr> <fct> <dbl> <chr> <dbl>
1 Alys… female 18.5 18 right right 92 left some never 173 metr… 18.2
2 Todd male 19.5 20.5 left right 104 left none regul 178. impe… 17.6
3 Gera… male 18 13.3 right left 87 neit… none occas NA <NA> 16.9
4 Robe… male 18.8 18.9 right right NA neit… none never 160 metr… 20.3
5 Dust… male 20 20 right neit… 35 right some never 165 metr… 23.7
6 Abby female 18 17.7 right left 64 right some never 173. impe… 21
7 Andre male 17.7 17.7 right left 83 right freq never 183. impe… 18.8
8 Mich… female 17 17.3 right right 74 right freq never 157 metr… 35.8
9 Edwa… male 20 19.5 right right 72 right some never 175 metr… 19
10 Carl male 18.5 18.5 right right 90 right some never 167 metr… 22.3
# … with 223 more rows, and abbreviated variable name ¹exercise
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